Fuzzy dynamic clustering algorithm

Pal, Sankar K. ; Mitra, Sushmita (1990) Fuzzy dynamic clustering algorithm Pattern Recognition Letters, 11 (8). pp. 525-535. ISSN 0167-8655

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Official URL: http://linkinghub.elsevier.com/retrieve/pii/016786...

Related URL: http://dx.doi.org/10.1016/0167-8655(90)90021-S


A three-stage dynamic fuzzy clustering algorithm consisting of initial partitioning, a sequence of updating and merging by optimisation of a characterisation function based on measures of fuzziness in a set is described. Unlike the conventional detection of disjoint initial clusters, the algorithm can extract overlapping initial cluster boundaries when the feature space has ill-defined regions. The membership function in Rn involves the density of patterns at a point in addition to its Euclidean distance. The merging criterion involves the number of samples and the amount of fuzziness in the intersection of two clusters, and the disparity in their size. The effectiveness of the algorithm is demonstrated on the speech recognition problem.

Item Type:Article
Source:Copyright of this article belongs to International Association for Pattern Recognition.
Keywords:Fuzzy Clustering; Measures of Fuzziness; Speech Recognition
ID Code:26108
Deposited On:06 Dec 2010 13:05
Last Modified:13 Jun 2011 06:07

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